ChloroMitoSSRDB 2.00: more genomes, more repeats, unifying SSRs search patterns and on-the-fly repeat detection.

Gaurav Sablok,Suresh B Mudunuri,Galina Yahubyan,G V Padma Raju,Peter J Ralph,Ratna Prabha,Dhananjaya P Singh,Nicola La Porta,Vesselin Baev

doi:10.1093/database/bav084

Abstract

Organelle genomes evolve rapidly as compared with nuclear genomes and have been widely used for developing microsatellites or simple sequence repeats (SSRs) markers for delineating phylogenomics. In our previous reports, we have established the largest repository of organelle SSRs, ChloroMitoSSRDB, which provides access to 2161 organelle genomes (1982 mitochondrial and 179 chloroplast genomes) with a total of 5838 perfect chloroplast SSRs, 37 297 imperfect chloroplast SSRs, 5898 perfect mitochondrial SSRs and 50 355 imperfect mitochondrial SSRs across organelle genomes. In the present research, we have updated ChloroMitoSSRDB by systematically analyzing and adding additional 191 chloroplast and 2102 mitochondrial genomes. With the recent update, ChloroMitoSSRDB 2.00 provides access to a total of 4454 organelle genomes displaying a total of 40 653 IMEx Perfect SSRs (11 802 Chloroplast Perfect SSRs and 28 851 Mitochondria Perfect SSRs), 275 981 IMEx Imperfect SSRs (78 972 Chloroplast Imperfect SSRs and 197 009 Mitochondria Imperfect SSRs), 35 250 MISA (MIcroSAtellite identification tool) Perfect SSRs and 3211 MISA Compound SSRs and associated information such as location of the repeats (coding and non-coding), size of repeat, motif and length polymorphism, and primer pairs. Additionally, we have integrated and made available several in silico SSRs mining tools through a unified web-portal for in silico repeat mining for assembled organelle genomes and from next generation sequencing reads. ChloroMitoSSRDB 2.00 allows the end user to perform multiple SSRs searches and easy browsing through the SSRs using two repeat algorithms and provide primer pair information for identified SSRs for evolutionary genomics.Database URL: http://www.mcr.org.in/chloromitossrdb

Highlights

Nuclear and organelle genome-based microsatellites or simple sequence repeats (SSRs) markers have been widely used to demonstrate the underpinning differences in genetic patterns and for assessing the phylogenomic and genetic associations between species of particular clade (1–3)
Realizing the ease of application, organelle genome markers have been widely applied for resolving the patterns of molecular evolutions, demographic and phylo-geographical diversity and to understand the genetic basis of species adaptions ranging from Pinus (8) to Oryza sativa (Monocots). (10, 11) Recent reports demonstrate the in silico identification of SSRs in organelle genomes of various organisms including plants. (12–15) the reported studies have focused on either relatively small number of organelle genomes or organelle genome representing a specific clade
Developed organelle repositories such as FUGOID (16), primer respository for chloroplast genomes (17), GOBASE (18) and AT_CHLORO (19), provides a wide array of curated information on certain aspects of organelle genomics, they lack SSRs information, which motivated the earlier establishment of ChloroMitoSSRDB (9), as an integrated open-access portal for browsing SSRs patterns from organelle genomes across several clades of organism

Summary

Introduction

Nuclear and organelle (chloroplast and mitochondrial) genome-based microsatellites or simple sequence repeats (SSRs) markers have been widely used to demonstrate the underpinning differences in genetic patterns and for assessing the phylogenomic and genetic associations between species of particular clade (1–3). Developed organelle repositories such as FUGOID (16), primer respository for chloroplast genomes (17), GOBASE (18) and AT_CHLORO (19), provides a wide array of curated information on certain aspects of organelle genomics, they lack SSRs information, which motivated the earlier establishment of ChloroMitoSSRDB (9), as an integrated open-access portal for browsing SSRs patterns from organelle genomes across several clades of organism. Following this approach, two SSRs repositories, namely MitoSatPlant (15) and ChloroSSRdb (20) have been developed focusing on plant species. The mere lack of this knowledge gap motivated us to develop ChloroMitoSSRDB 2.00, a sequel update to the ChloroMitoSSRDB

Methods

Results

Conclusion